Pedigree likelihood ratio for lineage markers

MPKin-YSTR: Interpretation of Y chromosome STR haplotypes for missing persons cases

Y chromosome Short Tandem Repeat (STR) haplotypes have been used in assisting forensic investigations primarily for identification and male lineage determination. The current SWGDAM interpretation guidelines for Y-STR typing provide helpful guidance on those purposes but do not address the issue of kinship analysis with Y-STR haplotypes. Because of the high mutation rate of Y-STRs, there are complex missing person cases in which inconsistent Y-STR haplotypes between true paternal lineage relatives will arise and cases with two or more male references in the same lineage and yet differ in their haplotypes. Therefore, more useful methods are needed for interpreting the Y-STR haplotype data. Computational methods and interpretation guidelines have been developed specifically addressing this issue, either using a mismatch-based counting method or a pedigree likelihood ratio method. In this study, a software program, MPKin-YSTR, was developed by implementing those more sophisticated methods. This software should be able to improve the interpretation of complex cases with Y-STR haplotype evidence. Thus, more biological evidence will be interpreted, which in turn will result in more investigation leads to help solve crimes.

Forensic investigation approaches of searching relatives in DNA databases

There are several indirect database searching approaches to identify the potential source of a forensic biological sample. These DNA-based approaches are familial searching, Y-STR database searching, and investigative genetic genealogy (IGG). The first two strategies use forensic DNA databases managed by the government, and the latter uses databases managed by private citizens or companies. Each of these search strategies relies on DNA testing to identify relatives of the donor of the crime scene sample, provided such profiles reside in the DNA database(s). All three approaches have been successfully used to identify the donor of biological evidence, which assisted in solving criminal cases or identifying unknown human remains. This paper describes and compares these approaches in terms of genotyping technologies, searching methods, database structures, searching efficiency, data quality, data security, and costs, and raises some potential privacy and legal considerations for further discussion by stakeholders and scientists. Y-STR database searching and IGG are advantageous since they are able to assist in more cases than familial searching readily identifying distant relatives. In contrast, familial searching can be performed more readily with existing laboratory systems. Every country or state may have its own unique economic, technical, cultural, and legal considerations and should decide the best approach(es) to fit those circumstances. Regardless of the approach, the ultimate goal should be the same: generate investigative leads and solve active and cold criminal cases to public safety, under stringent policies and security practices designed to protect the privacy of its citizenry.

Combined application of multiple autosomal and Y-chromosomal STR loci in solving a homicide case in 2009

In 2009, a violent murder occurred. Two victims, a 47-year-old mother and her 21-year-old daughter, were murdered at home. After importing the 20 autosomal STR loci and 27 Y-STR loci into a database, no hit had been found. In 2019, a person with a prior criminal record was matched in the national forensic Y-STR database. When increasing the number of detected Y-STR loci to 60, all loci of the bloodstain donor at the crime and the suspect were still found to be identical. With the combined calculation of multiple autosomal STR and kinship index, we were able to identify the perpetrator as a previously unknown illegitimate child of a large family and solved the case.

A convenient guideline to determine if two Y-STR profiles are from the same lineage

Y chromosome STR loci are used in forensics primarily for identification purposes by determining the male lineages. The Henan province in China has established a large Y-STR (>200 000 profiles) database for criminal investigations. A large proportion of the Y-STR profiles in the database were generated using either the Applied Biosystems Yfiler(ۛ) or Yfiler(ۛ) Plus PCR Amplification kits. The additional loci in the Yfiler Plus kit as compared to the Yfiler kit results in a concomitant cumulative mutation rate increase across the loci. Therefore, in those cases when two profiles have one to a few mismatched loci, it is difficult to determine if they are from the same lineage. In this study, 7405 unrelated male profiles were manually selected from the database. Analysis showed higher power of discrimination than the corresponding Yfiler haplotypes. Further, the distributions of the number of mismatched loci and the mismatched steps were generated for father-son, grandfather-grandson, uncle-nephew, and cousins (i.e. one, two, three, and four meioses, respectively) by exhaustive pairwise comparison of the unrelated profiles using a dynamic programming approach. The same distributions were generated for unrelated pairs with mutation rates of the loci. With the distributions, the false negative and false positive rates were determined. Two Yfiler profiles with ≤2 mismatched loci or ≤2 steps are more likely from the same lineage than unrelated lineages, and two Yfiler Plus profiles with ≤4 mismatched loci or ≤5 mismatched steps are more likely from the same lineage.

Use of prior odds for missing persons identifications

Identification of missing persons from mass disasters is based on evaluation of a number of variables and observations regarding the combination of features derived from these variables. DNA typing now is playing a more prominent role in the identification of human remains, and particularly so for highly decomposed and fragmented remains. The strength of genetic associations, by either direct or kinship analyses, is often quantified by calculating a likelihood ratio. The likelihood ratio can be multiplied by prior odds based on nongenetic evidence to calculate the posterior odds, that is, by applying Bayes' Theorem, to arrive at a probability of identity. For the identification of human remains, the path creating the set and intersection of variables that contribute to the prior odds needs to be appreciated and well defined. Other than considering the total number of missing persons, the forensic DNA community has been silent on specifying the elements of prior odds computations. The variables include the number of missing individuals, eyewitness accounts, anthropological features, demographics and other identifying characteristics. The assumptions, supporting data and reasoning that are used to establish a prior probability that will be combined with the genetic data need to be considered and justified. Otherwise, data may be unintentionally or intentionally manipulated to achieve a probability of identity that cannot be supported and can thus misrepresent the uncertainty with associations. The forensic DNA community needs to develop guidelines for objectively computing prior odds.